Vehicle state detection method and device, vehicle and storage medium

Abstract

The invention relates to a vehicle state detection method and device, a vehicle and a storage medium, and relates to the technical field of intelligent cabins, and the method comprises the steps that in response to a target driving mode selection operation, a target racing track is determined; in response to driving of the vehicle in the target driving mode, state detection information of the vehicle is sent in real time; wherein the state detection information is used for identifying whether the vehicle leaves the target racing track. The method can inform the user whether the vehicle is separated from the target racing track or not in real time, is higher in real-time performance, does not need an external device of a racing yard to shoot and recognize, and improves the recognition efficiency.

Description

Technical Field

[0001] The present disclosure relates to the technical field of intelligent cockpits, and particularly to a vehicle state detection method, device, vehicle, and storage medium. Background Art

[0002] With the development of new energy vehicles, many car owners can drive new energy vehicles to experience the race track. When the existing race track is lapped, a timer installed in the race track is used for timing, and cameras are installed to identify whether the vehicle has left the race track, so as to determine whether the vehicle is driving illegally.

[0003] The method of identifying whether a vehicle has left the race track in the above manner has low identification efficiency and poor real-time performance.

[0004] It should be noted that the information disclosed in the above background art section is only used to enhance the understanding of the background of the present disclosure, and thus may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0005] To overcome the problems existing in the related art, the present disclosure provides a vehicle state detection method, device, equipment, and storage medium.

[0006] According to the first aspect of the embodiments of the present disclosure, a vehicle state detection method is provided, including:

[0007] Responding to a target driving mode selection operation to determine a target race track;

[0008] Responding to the vehicle driving in the target driving mode, and real-time sending the state detection information of the vehicle;

[0009] Wherein, the state detection information is used to identify whether the vehicle has left the target race track.

[0010] In some exemplary embodiments of the present disclosure, the responding to a target driving mode selection operation to determine a target race track includes:

[0011] Responding to a target driving mode selection operation to obtain the initial position information of the vehicle;

[0012] Based on the initial position information, determining the adapted target race track from the race track database and determining the target race track data;

[0013] Wherein, the race track database includes the race track data of multiple pre-stored race tracks.

[0014] In some exemplary embodiments of the present disclosure, the responding to the vehicle driving in the target driving mode and real-time sending the state detection information of the vehicle includes:

[0015] Determine the target track data corresponding to the target track;

[0016] Obtain the positioning data of the vehicle;

[0017] In response to the vehicle driving in the target driving mode, based on the target track data and the positioning data, perform off-track state detection to obtain the state detection information;

[0018] Send the state detection information in real time.

[0019] In some exemplary embodiments of the present disclosure, the target track data includes: a plurality of track line segments and the line segment position data of each track line segment;

[0020] The positioning data includes: the point position data of at least one position point; each position point corresponds to a driving moment; the at least one position point is sorted according to the corresponding driving moment;

[0021] Among them, the performing off-track state detection based on the target track data and the positioning data to obtain the state detection information includes:

[0022] Based on the line segment position data of each track line segment and the point position data of the at least one position point, determine the vehicle state of each position point;

[0023] Judge whether there are consecutive multiple position points with the vehicle state being off-track state. If so, count the number of consecutive multiple position points and the driving period corresponding to the consecutive multiple position points;

[0024] In response to the number being greater than a preset number threshold and the duration of the driving period being less than a preset time threshold, determine the state detection information as the vehicle leaving the target track.

[0025] In some exemplary embodiments of the present disclosure, the first position point is any one of the at least one position point;

[0026] Among them, the determining the vehicle state of each position point based on the line segment position data of each track line segment and the point position data of the at least one position point includes:

[0027] Based on the point position data of the first position point and the line segment position data of each track line segment, determine the corresponding determination point and the position data of the determination point among the plurality of track line segments;

[0028] Based on the position data of the determination point, determine whether the determination point meets a preset matching rule;

[0029] In response to the determination point satisfying a preset matching rule, determine that the vehicle state at the first position point is a state of not leaving the track;

[0030] In response to the determination point not satisfying the preset matching rule, determine that the vehicle state at the first position point is the state of leaving the track.

[0031] In some exemplary embodiments of the present disclosure, the determining the corresponding determination point and the position data of the determination point among the plurality of track line segments based on the point position data of the first position point and the line segment position data of each track line segment includes:

[0032] Based on the point position data of the first position point and the line segment position data of each track line segment, determine an associated line segment group corresponding to the first position point; the associated line segment group includes at least one track line segment;

[0033] Calculate a plurality of straight-line distances from the first position point to the at least one track line segment;

[0034] Based on the plurality of straight-line distances, screen to obtain a bound track line segment; wherein, the bound track line segment is one of the at least one track line segment;

[0035] Based on the point position data of the first position point and the line segment position data of the bound track line segment, determine the determination point and the position data of the determination point.

[0036] In some exemplary embodiments of the present disclosure, the positioning data includes: one or any combination of real-time kinematic positioning data, geographic location positioning data, and interconnection positioning data;

[0037] Wherein, the interconnection positioning data is positioning data obtained by the vehicle from other terminal devices.

[0038] In some exemplary embodiments of the present disclosure, the performing a leaving-track state detection based on the target track data and the positioning data to obtain the state detection information includes:

[0039] Based on the target track data and the real-time kinematic positioning data, perform a leaving-track state detection to obtain first state detection information;

[0040] In response to the first state detection information indicating that the vehicle has left the target track, based on the geographic location positioning data and the target track data, perform a leaving-track state detection to obtain second state detection information;

[0041] Determine the second state detection information as the state detection information.

[0042] In some exemplary embodiments of the present disclosure, the performing of the off-track state detection based on the target track data and the positioning data to obtain the state detection information further includes:

[0043] In response to the second state detection information indicating that the vehicle has not left the target track, monitoring whether the first state detection information changes;

[0044] In response to the first state detection information changing to indicate that the vehicle has not left the target track, performing the off-track state detection based on the target track data and the real-time kinematic positioning data to obtain the state detection information.

[0045] In some exemplary embodiments of the present disclosure, the performing of the off-track state detection based on the target track data and the positioning data to obtain the state detection information further includes:

[0046] In response to the second state detection information indicating that the vehicle has left the target track, performing the off-track state detection based on the interconnection positioning data and the target track data to obtain the third state detection information;

[0047] Determining the third state detection information as the state detection information.

[0048] In some exemplary embodiments of the present disclosure, the performing of the off-track state detection based on the target track data and the positioning data to obtain the state detection information further includes:

[0049] In response to the third state detection information indicating that the vehicle has not left the target track, monitoring whether the first state detection information changes;

[0050] In response to the first state detection information changing to indicate that the vehicle has not left the target track, performing the off-track state detection based on the target track data and the real-time kinematic positioning data to obtain the state detection information.

[0051] In some exemplary embodiments of the present disclosure, the responding to the vehicle driving in the target driving mode and real-time sending the state detection information of the vehicle further includes:

[0052] Based on the positioning data of the vehicle and the target track data, determining a first moment when the vehicle starts the race and a second moment when the vehicle ends the race;

[0053] Wherein, the real-time sending of the state detection information includes:

[0054] During a target driving period from the first moment to the second moment, real-time sending the state detection information of the vehicle.

[0055] In some exemplary embodiments of the present disclosure, it further includes:

[0056] In response to the vehicle traveling in the target driving mode, display the real-time position of the vehicle traveling on the target track.

[0057] According to a second aspect of the embodiments of the present disclosure, there is provided a vehicle state detection device, including:

[0058] A track determination unit, configured to determine a target track in response to a target driving mode selection operation;

[0059] A state detection unit, configured to, in response to the vehicle traveling in the target driving mode, transmit the state detection information of the vehicle in real time;

[0060] Wherein, the state detection information is used to identify whether the vehicle deviates from the target track.

[0061] According to a third aspect of the embodiments of the present disclosure, there is provided a vehicle, including:

[0062] A processor;

[0063] A memory for storing instructions executable by the processor;

[0064] Wherein, the processor is configured to: implement the steps of any one of the vehicle state detection methods described in the first aspect above.

[0065] According to a fourth aspect of the embodiments of the present disclosure, there is provided a non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by a processor of a terminal, enabling the terminal to execute any one of the vehicle state detection methods described in the first aspect above.

[0066] According to a fifth aspect of the embodiments of the present disclosure, there is provided a computer program product, including a computer program, and when the computer program is executed by a processor, it implements any one of the vehicle state detection methods described in the first aspect above.

[0067] The technical solutions provided by the embodiments of the present disclosure may include the following beneficial effects:

[0068] The present disclosure determines a target track in response to a target driving mode selection operation, and when the vehicle is traveling in the target driving mode in the target track area, transmits the state detection information of the vehicle in real time to inform the user in real time whether the vehicle deviates from the target track. It is not only more real-time, but also does not require external devices in the racetrack to shoot and identify, improving the identification efficiency.

[0069] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. Description of the Drawings

[0070] The accompanying drawings herein are incorporated into and constitute a part of this specification, showing embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure.

[0071] Figure 1 is a flowchart of a vehicle state detection method shown according to an exemplary embodiment of the present disclosure Figure 1 .

[0072] Figure 2 is a flowchart of the implementation process of step S110 shown according to an exemplary embodiment of the present disclosure.

[0073] Figure 3 is the implementation process flow of step S120 shown according to an exemplary embodiment of the present disclosure Figure 1 .

[0074] Figure 4 is a flowchart of the implementation process of step S330 shown according to an exemplary embodiment of the present disclosure.

[0075] Figure 5 is a flowchart of the implementation process of step S410 shown according to an exemplary embodiment of the present disclosure.

[0076] Figure 6 is a flowchart of the implementation process of step S510 shown according to an exemplary embodiment of the present disclosure.

[0077] Figure 7 is a schematic diagram of the implementation of step S630 shown according to an exemplary embodiment of the present disclosure.

[0078] Figure 8 is a flowchart of a vehicle state detection method shown according to an exemplary embodiment of the present disclosure Figure 2 .

[0079] Figure 9 is the implementation process flow of a step S120 shown according to an exemplary embodiment of the present disclosure Figure 2 .

[0080] Figure 10 is the implementation process flow of a step S120 shown according to an exemplary embodiment of the present disclosure Figure 3 .

[0081] Figure 11 is the implementation process flow of a step S120 shown according to an exemplary embodiment of the present disclosure Figure 4 .

[0082] Figure 12 is the implementation process flow of a step S120 shown according to an exemplary embodiment of the present disclosureFigure 5 。

[0083] Figure 13 It is a schematic diagram of the positioning data of a track in a specific example shown according to an exemplary embodiment of the present disclosure.

[0084] Figure 14 It is a block diagram of a vehicle state detection device shown according to an exemplary embodiment of the present disclosure.

[0085] Figure 15 It is a block diagram of a vehicle shown according to an exemplary embodiment of the present disclosure. Detailed implementation manners

[0086] Here, some exemplary embodiments of the present disclosure will be described in detail, and examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. Various changes, modifications, and equivalents of the methods, devices, and / or systems described herein will become apparent after understanding the present disclosure. For example, the order of the operations described herein is merely an example and is not limited to those set forth herein, but may be changed as will be apparent after understanding the present disclosure, except for operations that must be performed in a specific order. Additionally, descriptions of features known in the art may be omitted for the sake of clarity and brevity.

[0087] The implementation manners described in some embodiments of the following exemplary embodiments of the present disclosure do not represent all implementation manners consistent with the present disclosure. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0088] The following will describe in detail the specific implementation manners of the embodiments of the present disclosure with reference to the drawings.

[0089] Figure 1 It is a flowchart of a vehicle state detection method shown according to an exemplary embodiment of the present disclosure Figure 1 , and the vehicle state detection method can be used in an electronic device, including a vehicle, and the vehicle can be a new energy vehicle.

[0090] Such as Figure 1 shown, it includes the following steps.

[0091] In step S110, in response to a target driving mode selection operation, a target track is determined.

[0092] In an exemplary implementation of the present disclosure, the target driving mode may be a track driving mode. When the vehicle is driving in the track driving mode, the vehicle can optimize its performance by adjusting the power system, suspension system, braking system, cooling system, driving assistance system, etc. to meet the requirements of the race.

[0093] For users who hope to drive the vehicle in a race form on the track, the intelligent cockpit system of the vehicle can provide the corresponding track driving mode to the users. By providing an application program APP to the users, after the users click to enter the APP and then click the button to turn on the track driving mode, the APP interface will show that the vehicle has entered the track driving mode and display the corresponding target track.

[0094] In an exemplary implementation of the present disclosure, a track database storing multiple pre-stored tracks is set in the vehicle system. Users can select the corresponding target track from the track database according to the track to be run, or the target track can be automatically recognized according to the location of the vehicle. The track data of each track is corresponding in the track database.

[0095] In step S120, in response to the vehicle driving in the target driving mode, the status detection information of the vehicle is sent in real time.

[0096] In an exemplary embodiment of the present disclosure, the status detection information is used to identify whether the vehicle has deviated from the target track. During the process of the vehicle driving in the target driving mode, the status detection information monitored in real time is sent to the user. Specifically, it can be displayed in real time on the in-vehicle screen. For example, on the APP interface, the status can be informed to the user by the color or shape of an icon. A green icon represents that the vehicle has not deviated from the target track and is driving normally; a red icon represents that the vehicle has deviated from the target track and is in an abnormal race state. Further, the HUD (Head Up Display) system can also be used to project the status detection information in front of the driver's line of sight to prompt the user. When the status detection information indicates that the vehicle has deviated from the target track, a voice broadcast can also be used to prompt the user that the current vehicle has deviated from the target track. It can be understood that the above multiple sending methods can also be combined to send the status detection information of the vehicle to the user in multiple ways, which should all be regarded as within the protection scope of the present disclosure.

[0097] It can be seen from the above steps that the vehicle status detection method provided in the embodiment of the present disclosure determines the target track by responding to the target driving mode selection operation, and when the vehicle is driving in the target track area in the target driving mode, the status detection information of the vehicle is sent in real time to inform the user in real time whether the vehicle has deviated from the target track. It is not only more real-time, but also does not require external devices in the racetrack to photograph and identify the status of the vehicle, improving the recognition efficiency during the race.

[0098] Figure 2 It is a flowchart showing the implementation process of step S110 according to an exemplary embodiment of the present disclosure. As Figure 2 shown, it includes the following steps.

[0099] In step S210, in response to a target driving mode selection operation, the initial position information of the vehicle is acquired.

[0100] In an exemplary embodiment of the present disclosure, the initial position information of the vehicle may be the geographical location where the vehicle is located when the user selects the target driving mode. It can be acquired by using RTK (Real-Time Kinematic) positioning technology, or by using the software development kit (SDK) provided by a third-party map service, or by a combination of both.

[0101] In step S220, based on the initial position information, a suitable target track is determined from the track database, and target track data is determined.

[0102] In an exemplary embodiment of the present disclosure, the track database includes track data of multiple pre-stored tracks. The track data of each pre-stored track includes corresponding geographical location information, which may be the longitude and latitude coordinates of the range where the pre-stored track is located. The pre-stored track close to the geographical location represented by the initial position information can be automatically matched from the track database based on the initial position information. It should be noted that if there are multiple close pre-stored tracks matched, the target track can be determined in combination with the user's track selection operation, which is not elaborated in this embodiment of the present disclosure.

[0103] In an exemplary embodiment of the present disclosure, the track data of each pre-stored track includes the route trajectory data of the pre-stored track. The route trajectory data is composed of multiple track line segments and several continuous trajectory positioning points to record the route trajectory of the track. The route trajectory data can be generated according to the relevant geometric data of the track, or can be obtained by recording the actual driving trajectory of the vehicle, or can be generated by obtaining the track trajectory data from the racing event organizer.

[0104] In an exemplary embodiment of the present disclosure, when driving a vehicle on a pre-stored track in advance, RTK can be used to acquire a continuous plurality of driving trajectory positioning points during this process to form the above-mentioned route trajectory data. The positioning data of each driving trajectory positioning point during the vehicle driving process is collected by RTK, and all the driving trajectory positioning points are connected into a line to obtain multiple track line segments. The positioning data of each driving trajectory positioning point may include longitude, latitude, heading angle, elevation, etc.

[0105] RTK is a high-precision satellite positioning technology that can provide centimeter-level positioning accuracy in real-time conditions. For example, the RTK data acquisition frequency can be 100hz (i.e., one positioning point is obtained every 10ms). RTK technology achieves high-precision positioning by using real-time differential corrections between a reference station and a rover. Among them, the reference station is fixed at a position with known coordinates, receives satellite signals, calculates the positioning error, and then transmits the error data to the rover in real-time. The rover (such as a vehicle) receives satellite signals and the error data from the reference station, combines the two, and performs real-time differential calculations to eliminate most of the positioning errors and obtain high-precision position information. By using RTK to obtain track data, the accuracy of the stored track data is ensured, thereby providing an accurate track benchmark for subsequent status detection and ensuring the accuracy of vehicle status detection results.

[0106] In an exemplary embodiment of the present disclosure, the track data of each pre-stored track may further include track-related information. For example, track name, track length (or number of laps on the track), track start coordinates, track end coordinates, track width, etc.

[0107] It can be understood that the above pre-stored tracks can be regular tracks used in publicly held racing events, or a drivable road can be customized according to user needs as a custom track, and the track data of this custom track is obtained through the actual driving trajectory record of the vehicle.

[0108] In an exemplary embodiment of the present disclosure, the track name of the target track can also be determined based on the received track selection operation of the user, and the target track data is obtained from the track database based on the track name as the benchmark for subsequent status detection.

[0109] Figure 3 It is a process of the implementation of step S120 shown in an exemplary embodiment of the present disclosure Figure 1 . As Figure 3 shown, it includes the following steps.

[0110] In step S310, the target track data corresponding to the target track is determined.

[0111] It should be noted that to determine the target track data corresponding to the target track, it can be obtained from the track database through the above various methods, which will not be elaborated here.

[0112] In step S320, the positioning data of the vehicle is obtained.

[0113] In some embodiments of the present disclosure, to obtain the positioning data of the vehicle in real-time, it can be obtained through RTK, or through SDK, or through other devices interconnected with the vehicle to obtain the positioning data, which is obtained according to actual needs, and the embodiments of the present disclosure do not make limitations here.

[0114] In step S330, in response to the vehicle traveling in the target driving mode, based on the target track data and the positioning data, a detection of the off-track state is performed to obtain state detection information.

[0115] In some embodiments of the present disclosure, during the process of the vehicle traveling in the target driving mode, based on the positioning data of the vehicle obtained in real time and in combination with the target track data, a continuous detection of the off-track state is performed to obtain the state detection information at each position point during the vehicle traveling process.

[0116] In step S340, the state detection information is sent in real time.

[0117] It should be noted that for the implementation of step S340, reference may be made to the implementation process of the above step S120. When the state detection information at the current position point is obtained, it is immediately sent to the user.

[0118] In some exemplary embodiments of the present disclosure, the target track data includes: a plurality of track line segments and the line segment position data of each track line segment. The positioning data includes: the point position data of at least one position point; each position point corresponds to a driving moment; and at least one position point is sorted according to the corresponding driving moment.

[0119] It should be noted that the positioning data may include the point position data of the current position point, or may include the point position data of at least one position point included in the driving process from the initial position point to the current position point. At least one position point is continuous and is sorted according to the corresponding driving moment. At least one position point can form the actual driving trajectory of the vehicle at the current driving moment.

[0120] In some embodiments of the present disclosure, the driving moment can be determined according to the time stamp field included in the obtained positioning data. The time stamp is used to identify the positioning moment, and at least one position point is sorted based on the time stamp. It can also be based on the moment when the vehicle obtains the point position data of the position point, recorded as an index, and at least one position point is sorted based on the index.

[0121] In this exemplary embodiment of the present disclosure, the implementation process of step S330 is as Figure 4 shown and includes the following steps.

[0122] In step S410, based on the line segment position data of each track line segment and the point position data of at least one position point, the vehicle state of each position point is determined.

[0123] It should be noted that the line position data of each track segment represents the route trajectory of the target track. By comparing the line position data of each track segment with the point position data of at least one position point, it is possible to determine whether the vehicle state of each position point among the at least one position point is in a state of leaving the track or not leaving the track.

[0124] In step S420, it is judged whether there are continuously multiple position points in a state of leaving the track. If so, the number of continuously multiple position points and the corresponding driving time period are counted.

[0125] It should be noted that the continuously multiple position points include the current position point. That is to say, it is judged whether there are continuously multiple position points from a certain position point to the current position point in a state of leaving the track. If there are the above continuously multiple position points, the number of points and the corresponding driving time period are counted.

[0126] For example, the current position point is the position point numbered 0221, and the vehicle states of the position points numbered from 0105 to 0221 are all in a state of leaving the track. The number of counted points is 117, and the duration of the corresponding driving time period is 0.6 seconds.

[0127] In step S430, in response to the number being greater than a preset number threshold and the duration of the driving time period being less than a preset time threshold, it is determined that the state detection information is that the vehicle has left the target track.

[0128] In some embodiments of the present disclosure, by judging that the number is greater than a preset number threshold and the duration of the driving time period is less than a preset time threshold, it is determined that the vehicle has left the target track to prevent false alarms, which can effectively filter out short-term and discontinuous deviation situations, avoid false alarms caused by instantaneous interference or small-scale offsets, and thus avoid frequent false alarms or prompts, enabling the user to focus on driving without being disturbed by too much invalid information.

[0129] Specifically, by setting reasonable thresholds, it is possible to avoid complex processing of each individual data point, but instead focus on processing those truly important continuous deviation events, thereby optimizing the use of computing resources. The set preset number threshold and preset time threshold should not only ensure the real-time nature of detection, that is, it is necessary to quickly judge that the vehicle has left the target track, but also ensure the accuracy of detection, and it cannot be determined that the vehicle has left the target track only relying on a very small part of the data. The specific values can be determined based on multiple experiments, and the embodiments of the present disclosure do not limit them here.

[0130] In some exemplary embodiments of the present disclosure, to reduce data storage and computing, it can be determined whether the current position point is in a state where the vehicle is off the track. If so, a time window up to the current position point can be set, the set duration of the time window is a preset time threshold, and the number of position points in the time window where the vehicle state is off the track is counted. If the number exceeds a preset number threshold, the state detection information at the current moment is that the vehicle is off the target track. This can ensure that during the judgment process, the number of position points stored and processed is reduced, reducing the unnecessary data storage and transmission burden, and also improving the judgment efficiency.

[0131] In some embodiments of the present disclosure, the first position point is any one of the above at least one position point. Taking the first position point as an example, the process of determining the vehicle state based on the point position data is described.

[0132] Figure 5 It is a flowchart showing the implementation process of step S410 according to an exemplary embodiment of the present disclosure. As Figure 5 shown, it includes the following steps.

[0133] In step S510, based on the point position data of the first position point and the line segment position data of each track line segment, the corresponding determination point and the position data of the determination point are determined among multiple track line segments.

[0134] In some embodiments of the present disclosure, the implementation process of step S510 is as Figure 6 shown, and it includes the following steps.

[0135] In step S610, based on the point position data of the first position point and the line segment position data of each track line segment, the associated line segment group corresponding to the first position point is determined.

[0136] It should be noted that the associated line segment group includes at least one track line segment. At least one track line segment that the first position point may be associated with is selected from all the track line segments included in the target track to form the associated line segment group.

[0137] In some embodiments of the present disclosure, all the track line segments included in the target track can be retrieved by dividing into grids, obtaining multiple grids and one or more track line segments corresponding to each grid. The first grid where the first position point is located and the 9 grids included in the nine-square grid centered on the first grid can be determined by the point position data of the first position point. All the track line segments corresponding to the 9 grids are determined as the associated line segment group.

[0138] It should be noted that the grid index is a technique for dividing a two-dimensional or three-dimensional space into regular grids (usually squares or cubes), and each grid cell stores the data objects (here referring to track segments) that intersect or are contained therein. In this way, the set of track segments that may be related to the query position can be quickly located without traversing all the data. In specific implementation, the grid size is a set value, which is 1.1 times the set maximum binding distance. The maximum binding distance can be, for example, 80m, 100m, 105m, and the specific value is not limited in the embodiments of the present disclosure. All grids intersecting a track segment save this track segment.

[0139] In step S620, calculate the multiple straight-line distances from the first position point to at least one track segment respectively.

[0140] In some embodiments of the present disclosure, traverse all the track segments in the associated segment group and calculate the straight-line distance from the first position point to each track segment. The calculation principle is as follows: When the projection position of the first position point is within the track segment: For each track segment, first calculate the perpendicular projection point of the straight line formed by the first position point and the two endpoints of the segment. If this projection point falls on this track segment, use the distance from the first position point to this perpendicular line as the straight-line distance. When the projection position of the first position point is outside the track segment: If the projection point is not on this track segment (that is, beyond the range of the two endpoints of the segment), it is necessary to calculate the distances from the first position point to the two endpoints of the segment respectively, and take the smaller one of the distances as the straight-line distance.

[0141] In step S630, based on the multiple straight-line distances, screen out the bound track segment.

[0142] It should be noted that the bound track segment is one of at least one track segment. The bound track segment closest to the first position point can be screened out from at least one track segment through the multiple straight-line distances.

[0143] In step S640, based on the point position data of the first position point and the segment position data of the bound track segment, determine the determination point and the position data of the determination point.

[0144] In specific implementation, after obtaining the bound track segment, it is necessary to verify whether this bound track segment is valid. It can be verified whether the projection distance from the first position point to the bound track segment is less than the above-set maximum binding distance. If it is less, it indicates that this bound track segment is valid; otherwise, it is invalid.

[0145] When the bound track segment is valid here, the determination point and the position data of the determination point can be determined. Specifically, the first position point can be projected onto the projection point of the bound track segment or the end point of the bound track segment as the determination point. If the projection position of the first position point is within the track segment, the projection point is used as the determination point, and the position data of the determination point is recorded; if the projection position of the first position point is outside the track segment, the end point with the smaller distance from the first position point to the two end points of the bound track segment is used as the determination point, and the position data of the determination point is recorded.

[0146] It can be understood that the determination point represents an equivalent point for determining the distance between the first position point and the bound track segment, so as to measure whether the distance between the first position point and the bound track segment meets the requirements, that is, whether the first position point is close enough to the bound track segment, so as to determine whether the first position point has deviated from the trajectory of the target track. Using the determination point to determine the distance between the first position point and the bound track segment is only an example of the present disclosure, and is not used to limit the protection scope of the present invention. It can also be determined by calculating the perpendicular distance between the first position point and the bound track segment, etc. The present disclosure will not elaborate here.

[0147] In some exemplary embodiments of the present disclosure, the implementation process of step S630 is as Figure 7 shown. Based on multiple straight-line distances and the direction angle of the first position point, the binding score corresponding to each track segment in at least one track segment can be calculated, and the track segment with the lowest binding score is selected as the bound track segment.

[0148] The specific binding score calculation rules may include: determining the first score according to the straight-line distance and a preset first scoring rule; calculating the angle difference based on the direction angle and the direction of the track segment, and determining the second score according to the angle difference and a preset second scoring rule; combining the first score and the second score to obtain the binding score corresponding to each track segment.

[0149] For example, the first scoring rule may be that the value of the straight-line distance is multiplied by a preset first proportionality coefficient to obtain the first score. Based on the direction angle of the first position point, the vehicle driving direction at the first position point can be determined. Combining the line segment direction of the track segment, the angle difference between the two directions can be calculated. The second scoring rule may be the following calculation formula:

[0150] Second score = (α - 10) / (180 - 10) × 30 × β 2

[0151] where 30 < α ≤ 180 represents the angle difference; β 2 represents the second proportionality coefficient, a constant, preset in advance. If α is less than or equal to 30 degrees, the second score is 0.

[0152] The first score and the second score can be added to obtain a binding score. It can be understood that by adjusting the values of the first proportional coefficient and the second proportional coefficient, the weights of the straight-line distance and the angular difference can be adaptively adjusted, so as to obtain a binding score that can be objectively measured.

[0153] As Figure 7 shown in the example, the straight-line distance from the first position point to a track line segment is 15, the first score is 15 multiplied by 0.8, which is 12, the second score is 5.3, and the obtained binding score is 17.3.

[0154] In step S520, based on the position data of the determination point, it is determined whether the determination point meets a preset matching rule.

[0155] In step S530, in response to the determination point meeting the preset matching rule, it is determined that the vehicle state at the first position point is the state of not leaving the track.

[0156] In step S540, in response to the determination point not meeting the preset matching rule, it is determined that the vehicle state at the first position point is the state of leaving the track.

[0157] In some exemplary embodiments of the present disclosure, the preset matching rule may be that the distance between the determination point and the first position point is less than or equal to an effective matching distance. The effective matching distance can be set in advance, for example, it can be values such as 20m, 22m, 25m, etc., and is set according to actual needs and is not limited herein. If the distance between the determination point and the first position point is less than or equal to the effective matching distance, it is determined that the vehicle state at the first position point is the state of not leaving the track; if the distance between the determination point and the first position point is greater than the effective matching distance, it is determined that the vehicle state at the first position point is the state of leaving the track.

[0158] In some exemplary embodiments of the present disclosure, the real-time position of the vehicle on the target track may also be displayed to the user for the user to visually view the current position. Figure 8 is a flowchart of a vehicle state detection method shown according to an exemplary embodiment of the present disclosure Figure 2 . Figure 8 Steps S810 to S820 in Figure 1 correspond to steps S110 to S120 in Figure 8 and will not be repeated here. As Figure 1 shown, based on the vehicle state detection method shown in

[0159] In step S830, in response to the vehicle traveling in the target driving mode, the real-time position of the vehicle traveling on the target track is displayed.

[0160] In an exemplary embodiment of the present disclosure, during the process of the vehicle driving in the target driving mode, while sending the state detection information monitored in real time to the user, the real-time position of the vehicle driving on the target track is displayed to the user based on the positioning data of the vehicle obtained in real time. It can be in the form of the vehicle moving on the track thumbnail in the form of an icon, and different perspectives can also be switched, such as the bird's-eye view, the driver's perspective, the top-down perspective, etc. Specifically, in combination with the environmental data collected by the vehicle's sensors, etc., the intelligent cockpit system can display the track picture from the driver's perspective, or both can be displayed on the in-vehicle screen at the same time to enhance the user experience. And the user is allowed to click on the track thumbnail through the touch screen to view the current real-time position and the relevant information of the target track.

[0161] In an exemplary embodiment of the present disclosure, the real-time position of the vehicle driving on the target track can also be displayed based on the state detection information of the current position. Specifically, if the state detection information of the current position indicates that the vehicle has deviated from the target track, the icon representing the vehicle will no longer be displayed in the track thumbnail.

[0162] In some exemplary embodiments of the present disclosure, the above positioning data includes one or any combination of real-time kinematic positioning data, geographic location positioning data, and interconnected positioning data.

[0163] It should be noted that the real-time kinematic positioning data is obtained by using RTK, and the geographic location positioning data is obtained through the software development kit (SDK) provided by a third-party map service. The third-party map service usually provides the positioning data of the vehicle based on satellite positioning systems such as GPS and Beidou, and combines auxiliary positioning technologies such as cellular networks. The interconnected positioning data is the positioning data obtained by the vehicle from other terminal devices. The other terminal devices are located inside the vehicle and are interconnected with the vehicle. That is, through the V2X (Vehicle-to-Everything) technology, the vehicle can exchange information and cooperate with various terminal devices. For example, devices such as smartphones and tablets can be placed in the vehicle's cockpit. The vehicle can be interconnected with these devices, and these devices are also equipped with positioning modules, which can obtain the positioning data of the terminal devices in real time and transmit it to the vehicle for use through communication technologies.

[0164] It can be understood that from the perspective of positioning accuracy, the real-time kinematic positioning data is better than the geographic location positioning data, and the geographic location positioning data is better than the interconnected positioning data. In specific implementation, the real-time kinematic positioning data can be preferentially used for the off-track state detection; when the real-time kinematic positioning data fails or an error occurs, the geographic location positioning data is used for the off-track state detection; when the geographic location positioning data fails or an error occurs, the interconnected positioning data is used for the off-track state detection.

[0165] In some embodiments of the present disclosure, real-time kinematic (RTK) positioning data, geographic location positioning data, and interconnection positioning data can be obtained simultaneously. When detecting the state of leaving the track, which positioning data to use can be determined according to the positioning accuracy. For example, the priority of the three types of data is RTK positioning data > geographic location positioning data > interconnection positioning data. RTK positioning data can be preferentially used for detecting the state of leaving the track. If the RTK positioning data fails or is incorrect, geographic location positioning data is used. If the geographic location positioning data fails or is incorrect, interconnection positioning data is used for detecting the state of leaving the track. Through comprehensive positioning data sources, the reliability of detecting the state of leaving the track is ensured.

[0166] Correspondingly, an example is used for illustration. Figure 9 is a process of the implementation of step S120 according to an exemplary embodiment of the present disclosure Figure 2 . As Figure 9 shown, it includes the following steps.

[0167] In step S910, based on the target track data and RTK positioning data, the state of leaving the track is detected to obtain the first state detection information.

[0168] In step S920, in response to the first state detection information indicating that the vehicle has left the target track, based on the geographic location positioning data and the target track data, the state of leaving the track is detected to obtain the second state detection information.

[0169] In step S930, the second state detection information is determined as the state detection information.

[0170] It should be noted that Figure 9 the shown implementation process is for the detection at the current position point. That is, based on the RTK positioning data at the current position point, the state of leaving the track is detected. If the obtained first state detection information indicates that the vehicle has left the target track, in order to avoid misjudgment caused by a malfunction in obtaining the positioning by RTK, the SDK technology is activated to obtain the geographic location positioning data, and the state of leaving the track at the current position point is detected again. The obtained second state detection information is determined as the state detection information.

[0171] It should be noted that in order to reduce the CPU computing power occupancy and unnecessary memory storage occupancy, when the first state detection information is determined to indicate that the vehicle has left the target track, the positioning function corresponding to the geographic location positioning data is activated, so as to reduce the amount of data that the vehicle processor needs to process, avoid delays caused by excessive data processing volume, and thus avoid state detection deviation.

[0172] In some embodiments of the present disclosure, the RTK positioning function keeps running continuously to obtain real-time kinematic positioning data without interruption, so that after it is determined that the real-time kinematic positioning data has returned to normal, the real-time kinematic positioning data is preferentially used for off-track state detection. Since in an open track scenario, RTK positioning usually has occasional anomalies and does not remain abnormal continuously. After other positioning functions are enabled, it will most likely return to normal after a few seconds to dozens of seconds.

[0173] Correspondingly, Figure 10 is a process of the implementation of step S120 shown in an exemplary embodiment of the present disclosure Figure 3 . Figure 10 Steps S1010 to S1030 in Figure 9 correspond to steps S910 to S930 in Figure 10 and will not be repeated here. As Figure 9 shown, based on the implementation process shown in

[0174] In step S1040, in response to the second state detection information indicating that the vehicle has not left the target track, monitor whether the first state detection information changes.

[0175] In step S1050, in response to the first state detection information changing to indicate that the vehicle has not left the target track, perform off-track state detection based on the target track data and the real-time kinematic positioning data to obtain state detection information.

[0176] It should be noted that after it is determined that the second state detection information at the second position point indicates that the vehicle has not left the target track and the first state detection information indicates that the vehicle has left the target track, during the driving process after the second position point, continuously monitor whether the first state detection information at subsequent position points changes and whether it changes to indicate that the vehicle has not left the target track. If the first state detection information at the third position point resumes to indicate that the vehicle has not left the target track, starting from this third position point, the subsequent off-track state detection uses the real-time kinematic positioning data, and the positioning function for obtaining geographical location positioning data is turned off to ensure that more accurate positioning data with higher precision is preferentially used to ensure the accuracy and precision of the vehicle state detection results.

[0177] Similar to the above exemplary embodiment, another example is used for illustration. Figure 11 is a process of the implementation of step S120 shown in an exemplary embodiment of the present disclosure Figure 4 . Figure 11 Steps S1110 to S1120 in Figure 9 correspond to steps S910 to S920 in Figure 11 and will not be repeated here. As Figure 9Based on the shown implementation process, the following steps are further included.

[0178] In step S1130, in response to the second state detection information indicating that the vehicle has left the target track, based on the interconnected positioning data and the target track data, a state detection for leaving the track is performed to obtain the third state detection information.

[0179] In step S1140, the third state detection information is determined as the state detection information.

[0180] It should be noted that Figure 11 the shown implementation process is for the detection at the current position point. That is, based on the geographical location positioning data of the current position point, a state detection for leaving the track is performed. If the obtained second state detection information indicates that the vehicle has left the target track, in order to avoid misjudgment caused by a malfunction of the geographical location positioning data, the technology of obtaining positioning through interconnection is activated to obtain the interconnected positioning data, and the state detection for leaving the track is re-performed on the current position point, and the obtained third state detection information is determined as the state detection information.

[0181] It should be noted that, in order to reduce the CPU computing power occupancy and unnecessary memory storage occupancy, when it is determined that the second state detection information indicates that the vehicle has left the target track, the function of obtaining positioning through interconnection is activated to reduce the amount of data that the vehicle processor needs to process and the data transmission volume, and avoid the delay caused by excessive data processing volume, thereby avoiding the resulting state detection deviation. And after activating the function of obtaining positioning through interconnection, the positioning function corresponding to the geographical location positioning data is turned off to reduce unnecessary data processing.

[0182] Similarly, the RTK positioning function keeps running to continuously obtain real-time kinematic positioning data, so that after it is determined that the real-time kinematic positioning data has returned to normal, the real-time kinematic positioning data is preferentially used for the state detection of leaving the track.

[0183] Correspondingly, Figure 12 is a process of the implementation of step S120 shown according to an exemplary embodiment of the present disclosure Figure 5 . Figure 12 Steps S1210 to S1240 in Figure 11 correspond to steps S1110 to S1140 in Figure 12 and will not be repeated here. As Figure 11 shown, based on the shown implementation process in

[0184] In step S1250, in response to the third state detection information indicating that the vehicle has not left the target track, it is monitored whether the first state detection information changes.

[0185] In step S1260, in response to the change of the first state detection information to the vehicle not leaving the target track, based on the target track data and the real-time kinematic positioning data, a detection of the state of leaving the track is performed to obtain the state detection information.

[0186] It should be noted that after it is determined that the third state detection information at the fourth position point is that the vehicle has not left the target track and the second state detection information is that the vehicle has left the target track, during the driving process after the fourth position point, continuously monitor whether the first state detection information at subsequent position points changes and whether it changes to the vehicle not leaving the target track. If the first state detection information at the fifth position point resumes to the vehicle not leaving the target track, starting from the fifth position point, the subsequent detection of the state of leaving the track uses the real-time kinematic positioning data, and the function of obtaining positioning through interconnection is turned off to ensure the priority use of more accurate positioning data to ensure the accuracy and precision of the vehicle state detection result.

[0187] In this embodiment, for the current position point, when the first state detection information, the second state detection information, and the third state detection information all indicate that the vehicle has left the target track, the final state detection information is obtained as the vehicle has left the target track to ensure the accuracy of the vehicle state detection result.

[0188] It can be understood that most of the tracks in a racing competition are repetitive lap tracks, and it is necessary to drive repeatedly on the same lap track, record the time used for each lap and the total time. In order to improve the performance, generally, the vehicle is allowed to drive a warm-up lap on the track and then start timing to indicate the start of the race. At the end, to ensure the safety of the race, generally, the vehicle is allowed to drive a cooling lap on the track and then drive to a non-race area.

[0189] In some embodiments of the present disclosure, based on the above race rules, the first moment when the vehicle starts the race and the second moment when the vehicle ends the race can be determined based on the positioning data of the vehicle and the target track data. During the target driving period from the first moment to the second moment, the state detection information of the vehicle is sent in real time. That is to say, during an actual race, the state detection information of the vehicle is sent to the user to prompt the user to pay attention to whether the vehicle leaves the track, while in other stages, such as the driving stages of the cooling lap and the warm-up lap, there is no need to perform state detection, nor to remind the user to pay attention. On the one hand, it reduces the workload of the vehicle processor, and on the other hand, it provides a precise prompt service for the user, avoiding ineffective prompts from interfering with the user and affecting the user experience.

[0190] Now, a specific example of applying the vehicle state detection provided by the embodiments of the present disclosure is provided to further explain and illustrate.

[0191] This specific example provides a vehicle. The vehicle is equipped with various units such as an RTK high-precision positioning unit, a track data maintenance unit, a low-precision positioning unit, an enhanced positioning unit, and a track departure detection unit. The work and cooperation of these units realize the state detection of the vehicle, and the detection results are displayed on the in-vehicle display interface.

[0192] The RTK high-precision positioning unit includes a hardware part and a software part. The hardware part supports RTK technology, and the software part obtains RTK high-precision positioning data and transmits it to the track data maintenance unit during track pre-storage.

[0193] It should be noted that the RTK high-precision positioning data obtained by the track data maintenance unit not only depends on the RTK high-precision positioning unit set on the vehicle, but also can be based on the RTK high-precision positioning data obtained by other devices carried on the vehicle, and can also obtain the RTK high-precision positioning data stored in the cloud.

[0194] During track pre-storage, the vehicle travels on the real track. Based on the complete track driving process, the track data maintenance unit processes the RTK high-precision positioning data of each positioning point and stores it in the track database in the form of track line segments. For subsequent data update, maintenance and other processing, it can also include: storage time, timestamp.

[0195] It should be noted that usually thousands or tens of thousands of RTK positioning points are included in a track. The relevant data of each positioning point can be stored in the form of an array, and for continuous positioning points, they are separated by "|". As Figure 13 shown, it is a schematic diagram of the positioning data of a track processed by the track data maintenance unit. The data source of the points connected into a line is RTK, and the discrete points are positioning points obtained based on Amap, which are from the low-precision positioning unit.

[0196] A third-party navigation and positioning software is integrated in the vehicle. The low-precision positioning unit obtains data such as "longitude", "latitude", and "timestamp" through the interface provided by the third-party software. Through Figure 13 It can also be seen that the RTK data has a high frequency, high density, is smoother and more accurate than the Amap data, and when the vehicle travels to the same position, the RTK data can be measured first, and the Amap data can be obtained approximately more than 500 milliseconds later.

[0197] The track departure detection unit continuously detects whether the vehicle departs from the track during the race. The track departure detection unit is electrically connected to the RTK high-precision positioning unit to obtain the real-time position of the vehicle during the race. If the detection result is that the vehicle departs from the track, the data obtained by the low-precision positioning unit is used for detection instead.

[0198] When a request is received, the low-precision positioning unit is started. The positioning logic of the low-precision positioning unit is the same as that of RTK, which can obtain positioning data such as longitude and latitude in real time and send it back to the off-track detection unit.

[0199] If it is continuously recognized that the vehicle has not left the track, the low-precision positioning unit will continue to be used until the detection result obtained from the positioning data acquired by the RTK high-precision positioning unit indicates that the vehicle has not left the track.

[0200] When the positioning data obtained by the low-precision positioning unit also indicates that the vehicle has left the track, in order to ensure the correctness of track recognition, the enhanced positioning function is used, that is, the enhanced positioning unit is used to obtain new positioning data.

[0201] There are devices such as mobile phones and tablets in the vehicle cockpit. The in-vehicle system in the vehicle can be connected to these electronic devices, and through interconnection, the vehicle can establish a communication connection with one of the electronic devices.

[0202] Taking the mobile phone as an example, the mobile phone is built-in with an interconnection service, which obtains the longitude and latitude data returned by the positioning module in the mobile phone and sends it to the enhanced positioning unit through the interconnection service. The enhanced positioning unit reads the positioning data sent back by the mobile phone and transmits it to the off-track detection unit for detection until the detection result obtained from the positioning data acquired by the RTK high-precision positioning unit indicates that the vehicle has not left the track.

[0203] If it is recognized that the vehicle has left the track through RTK, low-precision positioning, enhanced positioning, etc., it is determined that the vehicle has left the track.

[0204] When the user is driving the vehicle in a race, it can accurately identify whether the vehicle deviates from the track, ensuring the accuracy, fairness, and automation of lap timing and monitoring on the track.

[0205] It should be noted that in the technical solution of the present disclosure, the acquisition, storage, use, processing, etc. of information or data all comply with the relevant regulations of national laws and regulations.

[0206] Figure 14 It is a block diagram of a vehicle state detection device shown in some exemplary embodiments of the present disclosure. Referring to Figure 14 , the device 1400 includes: a track determination unit 1401 and a state detection unit 1402.

[0207] The track determination unit 1401 is configured to determine a target track in response to a target driving mode selection operation;

[0208] The state detection unit 1402 is configured to send real-time vehicle state detection information in response to the vehicle driving in the target driving mode;

[0209] Among them, the status detection information is used to identify whether the vehicle has left the target track.

[0210] In some exemplary embodiments of the present disclosure, the track determination unit 1401 is configured to:

[0211] In response to a target driving mode selection operation, obtain the initial position information of the vehicle;

[0212] Based on the initial position information, determine an adapted target track from the track database and determine target track data;

[0213] Among them, the track database includes track data of multiple pre-stored tracks.

[0214] In some exemplary embodiments of the present disclosure, the provided vehicle status detection device further includes: a display unit, configured to: in response to the vehicle driving in the target driving mode, display the real-time position of the vehicle on the target track.

[0215] In some exemplary embodiments of the present disclosure, the status detection unit 1402 is configured to:

[0216] Based on the positioning data of the vehicle and the target track data, determine the first moment when the vehicle starts the race and the second moment when the vehicle ends the race;

[0217] During the target driving period from the first moment to the second moment, transmit the status detection information of the vehicle in real time.

[0218] In some exemplary embodiments of the present disclosure, the status detection unit 1402 is configured to:

[0219] Determine the target track data corresponding to the target track;

[0220] Obtain the positioning data of the vehicle;

[0221] In response to the vehicle driving in the target driving mode, based on the target track data and the positioning data, perform off-track status detection to obtain status detection information;

[0222] Transmit the status detection information in real time.

[0223] In some exemplary embodiments of the present disclosure, the target track data includes: a plurality of track line segments and the line segment position data of each track line segment; the positioning data includes: the point position data of at least one position point; each position point corresponds to a driving moment; and at least one position point is sorted according to the corresponding driving moment.

[0224] In some exemplary embodiments of the present disclosure, the status detection unit 1402 is configured to:

[0225] Determine the vehicle state of each position point based on the line segment position data of each track segment and the point position data of at least one position point;

[0226] Determine whether there are consecutive multiple position points with the vehicle state being off the track state. If so, count the number of consecutive multiple position points and the corresponding driving time period of the consecutive multiple position points;

[0227] In response to the number being greater than a preset number threshold and the duration of the driving time period being less than a preset time threshold, determine that the status detection information is that the vehicle has left the target track.

[0228] In some exemplary embodiments of the present disclosure, the status detection unit 1402 is configured to:

[0229] Based on the point position data of the first position point and the line segment position data of each track segment, determine the corresponding determination point and the position data of the determination point among multiple track segments;

[0230] Based on the position data of the determination point, determine whether the determination point meets a preset matching rule;

[0231] In response to the determination point meeting the preset matching rule, determine that the vehicle state of the first position point is not off the track state;

[0232] In response to the determination point not meeting the preset matching rule, determine that the vehicle state of the first position point is off the track state.

[0233] It should be noted that the first position point is any one of at least one position point.

[0234] In some exemplary embodiments of the present disclosure, the status detection unit 1402 is specifically configured to:

[0235] Based on the point position data of the first position point and the line segment position data of each track segment, determine the associated line segment group corresponding to the first position point; the associated line segment group includes at least one track segment;

[0236] Calculate the multiple straight-line distances from the first position point to at least one track segment respectively;

[0237] Based on the multiple straight-line distances, screen and obtain the bound track segment; wherein, the bound track segment is one of at least one track segment;

[0238] Based on the point position data of the first position point and the line segment position data of the bound track segment, determine the determination point and the position data of the determination point.

[0239] It should be noted that the positioning data includes: one or any combination of real-time kinematic positioning data, geographic location positioning data, and interconnected positioning data. Among them, the interconnected positioning data is the positioning data obtained by the vehicle from other terminal devices.

[0240] In some exemplary embodiments of the present disclosure, the state detection unit 1402 is configured to:

[0241] Based on the target track data and real-time kinematic positioning data, perform off-track state detection to obtain first state detection information;

[0242] In response to the first state detection information indicating that the vehicle has left the target track, based on the geographic location positioning data and the target track data, perform off-track state detection to obtain second state detection information;

[0243] Determine the second state detection information as the state detection information.

[0244] In some exemplary embodiments of the present disclosure, the state detection unit 1402 is configured to:

[0245] In response to the second state detection information indicating that the vehicle has not left the target track, monitor whether the first state detection information changes;

[0246] In response to the first state detection information changing to indicate that the vehicle has not left the target track, based on the target track data and real-time kinematic positioning data, perform off-track state detection to obtain the state detection information.

[0247] In some exemplary embodiments of the present disclosure, the state detection unit 1402 is configured to:

[0248] In response to the second state detection information indicating that the vehicle has left the target track, based on the interconnected positioning data and the target track data, perform off-track state detection to obtain third state detection information;

[0249] Determine the third state detection information as the state detection information.

[0250] In some exemplary embodiments of the present disclosure, the state detection unit 1402 is configured to:

[0251] In response to the third state detection information indicating that the vehicle has not left the target track, monitor whether the first state detection information changes;

[0252] In response to the first state detection information changing to indicate that the vehicle has not left the target track, based on the target track data and real-time kinematic positioning data, perform off-track state detection to obtain the state detection information.

[0253] Regarding the device in the above embodiments, the specific manner in which each unit performs operations has been described in detail in the embodiments related to the method, and will not be elaborated here.

[0254] Figure 15 FIG. is a block diagram of a vehicle 1500 shown according to an exemplary embodiment. For example, the vehicle 1500 can be a hybrid vehicle, or a non - hybrid vehicle, an electric vehicle, a fuel cell vehicle, or other types of vehicles. The vehicle 1500 can be an autonomous vehicle, a semi - autonomous vehicle, or a non - autonomous vehicle.

[0255] Referring to Figure 15 , the vehicle 1500 can include various subsystems. For example, the infotainment system 1510, the perception system 1520, the decision - making and control system 1530, the drive system 1540, and the computing platform 1550. Among them, the vehicle 1500 can also include more or fewer subsystems, and each subsystem can include multiple components. In addition, each subsystem and each component of the vehicle 1500 can be interconnected by wired or wireless means.

[0256] In some embodiments, the infotainment system 1510 can include a communication system, an entertainment system, and a navigation system, etc.

[0257] The perception system 1520 can include several sensors for sensing information about the environment around the vehicle 1500. For example, the perception system 1520 can include a global positioning system (the global positioning system can be a GPS system, or a Beidou system, or other positioning systems), an inertial measurement unit (IMU), lidar, millimeter - wave radar, ultrasonic radar, and a camera device.

[0258] The decision - making and control system 1530 can include a computing system, a vehicle controller, a steering system, an accelerator, and a braking system.

[0259] The drive system 1540 can include components that provide power for the vehicle 1500 to move. In one embodiment, the drive system 1540 can include an engine, an energy source, a transmission system, and wheels. The engine can be one or a combination of an internal combustion engine, an electric motor, and an air - compression engine. The engine can convert the energy provided by the energy source into mechanical energy.

[0260] Some or all of the functions of the vehicle 1500 are controlled by the computing platform 1550. The computing platform 1550 can include at least one processor 1551 and a memory 1552. The processor 1551 can execute instructions 1553 stored in the memory 1552.

[0261] The processor 1551 can be any conventional processor, such as a commercially available CPU. The processor may also include, for example, a data processor (Graphic Process Unit, GPU), a field programmable gate array (Field Programmable Gate Array, FPGA), a system on chip (System on Chip, SOC), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or a combination thereof.

[0262] The memory 1552 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0263] In addition to the instructions 1553, the memory 1552 can also store data, such as road maps, route information, data on the position, direction, speed, etc. of the vehicle. The data stored in the memory 1552 can be used by the computing platform 1550.

[0264] In the embodiments of the present disclosure, the processor 1551 can execute the instructions 1553 to complete all or part of the steps of the above vehicle state detection method.

[0265] In some embodiments of the present disclosure, a non-transitory computer-readable storage medium is provided. When the instructions in the storage medium are executed by a processor of a vehicle, the vehicle can execute the above vehicle state detection method.

[0266] In some embodiments of the present disclosure, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the above vehicle state detection method is implemented.

[0267] Those skilled in the art will readily conceive of other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common general knowledge or conventional technical means in the technical field not disclosed in the present disclosure. The specification and embodiments are only to be considered as exemplary, and the true scope and spirit of the present disclosure are pointed out by the following claims.

[0268] It should be understood that the present disclosure is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present disclosure is only limited by the appended claims.

Claims

1. A vehicle state detection method, characterized in that: include: In response to a target driving mode selection operation, determining a target race track; In response to the vehicle traveling in the target driving mode, sending status detection information of the vehicle in real time; The state detection information is used to identify whether the vehicle has left the target track.

2. The vehicle state detection method according to claim 1, characterized in that: In response to the vehicle traveling in the target driving mode, sending the state detection information of the vehicle in real time includes: Determining target track data corresponding to the target track; Acquiring positioning data of the vehicle; In response to the vehicle traveling in the target driving mode, performing off-track state detection based on the target track data and the positioning data to obtain the state detection information; The status detection information is sent in real time.

3. The vehicle state detection method according to claim 2, characterized in that: The target track data includes: a plurality of track segments and segment position data of each track segment; The positioning data includes: point location data of at least one location point; each location point corresponds to a driving time; the at least one location point is sorted according to the corresponding driving time; The step of performing off-track state detection based on the target track data and the positioning data to obtain the state detection information includes: Determine the vehicle state of each position point based on the line segment position data of each track line segment and the point position data of the at least one position point; Determine whether there are multiple consecutive position points where the vehicle state is off the track, and if so, count the number of the multiple consecutive position points and the driving time periods corresponding to the multiple consecutive position points; In response to the number being greater than a preset number threshold and the duration of the driving period being less than a preset time threshold, it is determined that the state detection information is that the vehicle has deviated from the target track.

4. The vehicle state detection method according to claim 3, characterized in that: The first position point is any one of the at least one position point; Wherein, determining the vehicle state of each position point based on the line segment position data of each track line segment and the point position data of the at least one position point comprises: Based on the point position data of the first position point and the segment position data of each track segment, determining corresponding determination points and the position data of the determination points in the plurality of track segments; Based on the position data of the decision point, determining whether the decision point satisfies a preset matching rule; In response to the determination point satisfying a preset matching rule, determining that the vehicle state at the first position point is a state of not leaving the track; In response to the determination point not satisfying a preset matching rule, the vehicle state at the first position point is determined to be the off-track state.

5. The vehicle state detection method according to claim 4, characterized in that: The step of determining corresponding decision points and the position data of the decision points in the plurality of track segments based on the point position data of the first position point and the segment position data of each track segment comprises: Based on the point position data of the first position point and the line segment position data of each track line segment, determining an associated line segment group corresponding to the first position point; the associated line segment group includes at least one track line segment; Calculating a plurality of straight-line distances from the first position point to the at least one track segment respectively; Based on the multiple straight-line distances, a bound track segment is obtained by screening; wherein the bound track segment is one of the at least one track segment; The determination point and the position data of the determination point are determined based on the point position data of the first position point and the segment position data of the bound track segment.

6. The vehicle state detection method according to claim 2, characterized in that: The positioning data includes: one or any combination of real-time dynamic positioning data, geographic location positioning data, and interconnected positioning data; Among them, the interconnected positioning data is the positioning data obtained by the vehicle from other terminal devices.

7. The vehicle state detection method according to claim 6, characterized in that: The performing off-track state detection based on the target track data and the positioning data to obtain the state detection information includes: Based on the target track data and the real-time dynamic positioning data, performing off-track state detection to obtain first state detection information; In response to the first state detection information that the vehicle is off the target track, performing off-track state detection based on the geographic location data and the target track data to obtain second state detection information; The second state detection information is determined as the state detection information.

8. The vehicle state detection method according to claim 7, characterized in that: The performing off-track state detection based on the target track data and the positioning data to obtain the state detection information further includes: In response to the second state detection information indicating that the vehicle has not left the target track, monitoring whether the first state detection information has changed; In response to the first state detection information being changed to indicate that the vehicle has not deviated from the target track, a track deviated state detection is performed based on the target track data and the real-time dynamic positioning data to obtain the state detection information.

9. The vehicle state detection method according to claim 7, characterized in that: The performing off-track state detection based on the target track data and the positioning data to obtain the state detection information further includes: In response to the second state detection information that the vehicle is off the target track, performing off-track state detection based on the interconnected positioning data and the target track data to obtain third state detection information; The third state detection information is determined as the state detection information.

10. The vehicle state detection method according to claim 9, characterized in that: The performing off-track state detection based on the target track data and the positioning data to obtain the state detection information further includes: In response to the third state detection information indicating that the vehicle has not left the target track, monitoring whether the first state detection information has changed; In response to the first state detection information being changed to indicate that the vehicle has not deviated from the target track, a track deviated state detection is performed based on the target track data and the real-time dynamic positioning data to obtain the state detection information.

11. The vehicle state detection method according to claim 2, characterized in that: In response to the vehicle traveling in the target driving mode, sending the state detection information of the vehicle in real time also includes: Determine a first time when the vehicle starts a race and a second time when the vehicle ends a race based on the positioning data of the vehicle and the target track data; The real-time sending of the status detection information includes: During the target driving period from the first moment to the second moment, the state detection information of the vehicle is sent in real time.

12. The vehicle state detection method according to claim 1, characterized in that: In response to the target driving mode selection operation, determining the target track includes: In response to a target driving mode selection operation, acquiring initial position information of the vehicle; Determine the target track to be adapted from a track database based on the initial position information, and determine the target track data; The track database includes track data of multiple pre-stored tracks.

13. The vehicle state detection method according to claim 1, characterized in that: Also includes: In response to the vehicle being driven in the target driving mode, a real-time position of the vehicle being driven on the target track is displayed.

14. A vehicle state detection device, characterized in that: include: a track determination unit, configured to determine a target track in response to a target driving mode selection operation; a state detection unit, configured to send state detection information of the vehicle in real time in response to the vehicle traveling in the target driving mode; The state detection information is used to identify whether the vehicle has left the target track.

15. A vehicle, characterized in that: include: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to: implement the steps of the vehicle state detection method described in any one of claims 1 to 13.

16. A non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by a processor of a terminal, the terminal is enabled to perform the steps of a vehicle state detection method according to any one of claims 1 to 13.

17. A computer program product, characterized in that The invention comprises a computer program, which implements the vehicle state detection method according to any one of claims 1 to 13 when being executed by a processor.

Images